Statin Toxicity From Macrolide Antibiotic Coprescription
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Clarithromycin and erythromycin, but not azithromycin, inhibit cytochrome P450 isoenzyme 3A4 (CYP3A4), and inhibition increases blood concentrations of statins that are metabolized by CYP3A4. OBJECTIVE: To measure the frequency of statin toxicity after coprescription of a statin with clarithromycin or erythromycin. DESIGN: Population-based cohort study. SETTING: Ontario, Canada, from 2003 to 2010. PATIENTS: Continuous statin users older than 65 years who were prescribed clarithromycin (n = 72,591) or erythromycin (n = 3267) compared with those prescribed azithromycin (n = 68,478). MEASUREMENTS: The primary outcome was hospitalization with rhabdomyolysis within 30 days of the antibiotic prescription. RESULTS: Atorvastatin was the most commonly prescribed statin (73%) followed by simvastatin and lovastatin. Compared with azithromycin, coprescription of a statin with clarithromycin or erythromycin was associated with a higher risk for hospitalization with rhabdomyolysis (absolute risk increase, 0.02% [95% CI, 0.01% to 0.03%]; relative risk [RR], 2.17 [CI, 1.04 to 4.53]) or with acute kidney injury (absolute risk increase, 1.26% [CI, 0.58% to 1.95%]; RR, 1.78 [CI, 1.49 to 2.14]) and for all-cause mortality (absolute risk increase, 0.25% [CI, 0.17% to 0.33%]; RR, 1.56 [CI, 1.36 to 1.80]). LIMITATIONS: Only older adults were included in the study. The absolute risk increase for rhabdomyolysis may be underestimated because the codes used to identify it were insensitive. CONCLUSION: In older adults, coprescription of clarithromycin or erythromycin with a statin that is metabolized by CYP3A4 increases the risk for statin toxicity. PRIMARY FUNDING SOURCE: Academic Medical Organization of Southwestern Ontario.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it